Deskripsi

Nama Mahasiswa: Nama Lengkap Anda
NIM: Nomor Induk Mahasiswa Anda

Tujuan Analisis: Dokumen ini bertujuan untuk mengeksplorasi dan menganalisis data melalui visualisasi, guna mendapatkan wawasan yang dapat mendukung pengambilan keputusan.

# Load library
library(ggplot2)
library(readxl)

# Baca dataset
df <- read_excel("Data.xlsx")

# Periksa nama kolom
colnames(df)
## [1] "geo"                   "Negara"                "Benua"                
## [4] "Tahun"                 "Angka_Harapan_Hidup"   "Pendapatan_per_kapita"
## [7] "Populasi"              "Jumlah_anak"
# Plot histogram
ggplot(df, aes(x = Angka_Harapan_Hidup)) +
  geom_histogram(binwidth = 5, fill = "skyblue", color = "black") +
  labs(
    title = "Distribusi Angka Harapan Hidup",
    x = "Angka Harapan Hidup",
    y = "Frekuensi"
  ) +
  theme_minimal()

# Scatter plot
ggplot(df, aes(x = Pendapatan_per_kapita, y = Angka_Harapan_Hidup)) +
  geom_point(color = "blue", alpha = 0.7) +
  labs(
    title = "Hubungan Pendapatan per Kapita dan Angka Harapan Hidup",
    x = "Pendapatan per Kapita",
    y = "Angka Harapan Hidup"
  ) +
  theme_minimal()

library(ggplot2)
ggplot(df, aes(x = Tahun, y = Negara, fill = Angka_Harapan_Hidup)) +
  geom_tile() +
  scale_fill_gradient(low = "blue", high = "red") +
  labs(
    title = "Heatmap Angka Harapan Hidup",
    x = "Tahun",
    y = "Negara",
    fill = "Harapan Hidup"
  ) +
  theme_minimal()

# Scatter plot interaktif
library(plotly)
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
plot_ly(
  df, x = ~Pendapatan_per_kapita, y = ~Angka_Harapan_Hidup,
  type = "scatter", mode = "markers",
  color = ~Benua, text = ~paste("Negara:", Negara)
)